Ultrasound energy is reflected from macroscopic tissue interfaces returning specular reflections, for example, the interface between blood and muscle, and from microscopic components (scatterers) such as cell walls. Both macroscopic interfaces and microscopic scatterers represent acoustic impedance changes which reflect ultrasound energy. Conventional ultrasound images primarily display specular reflections. However, analysis of the characteristics of ultrasound energy reflected from scatterers, as related to tissue type, is preferable for diagnostic purposes.
Constructive and destructive interference among sound waves reflected from various scatterers produces an amplitude modulation of the returned ultrasound signal. Prior art systems can not measure this amplitude modulation on small spatial scales.
Although some of the prior art allows for certain crude morphologic features of tissue to be identified, such as size, thickness, and shape (see, Feigenbaum, H.; Echocardiography, 4e, Lea & Febiger (Philadelphia, 1986)), this identification is based on specular reflections. The prior art does not, in most instances, allow for the accurate or adequate characterization of the various scatterers within the tissue in enough detail to make firm diagnoses of the underlying pathology. For example, the only way to tell that heart muscle may have been damaged has been by observing the muscle thickness and shape as the heart beats. Current ultrasound technology does not permit clear distinction between normal and abnormal heart tissue, or allow discrimination of degrees of abnormality. Hence it is difficult to characterize, for example, heart muscle as normal, damaged, or non-living.
Another example of considerable clinical importance consists of the non-invasive classification of breast masses as either benign fibrous tissue or tumors.
The prior art makes use of analog ultrasonic radio frequency data by applying basic analog signal processing techniques to same. These techniques transform the analog signal data into a visual picture for clinical interpretation. Quantification can only be applied to shape, size, and thickness as seen on the visual image. Hence much information about the intrinsic characteristics of the microscopic scatterers within a given tissue or region of tissue is unavailable by the use of the prior art techniques.
Other prior art systems make use of the ultrasonic radio frequency data by applying various mathematical methods to the radio frequency signal to derive a number representing the total amount of reflected ultrasonic energy reaching the transducer (integrated backscatter). In in vitro testing, the integrated backscatter (IB) can be closely related to the reflectance of the tissue and appears to provide a useful discriminator (Miller JG, Perez JE, Sobel BE. "Ultrasonic characterization of myocardium." Progress In Cardiovascular Disease, 28:85-110, 1985). However, the IB in clinical situations depends heavily on the amount of power reaching the tissue and the amount of reflected power reaching the transducer. Both factors depend critically upon unknown variables (e.g., attenuation and scatter in the tissue between the transducer and the region of interest). Thus, in order for measurement of IB to be clinically applicable, it requires calibration with an external reference standard (such as a steel plate reflector). Because external calibration cannot be applied to an in vivo situation, many assumptions and estimates concerning tissue absorption must be made, consequently limiting the utility of IB analysis.
U.S. Pat. No. 4,817,015 of Insana et al. provides a method for discriminating between different tissue textures within conventionally processed analog images of the returned ultrasound signals. Insana assumes a single, well-defined spatial texture scale, adds linear and higher order statistical terms, and subtracts an estimated noise curve to locate features within a 4-dimensional feature space. The underlying assumptions built into the Insana system provide many potential sources of error.
Similarly, the system taught in U.S. Pat. No. Re. 33,672 of Miwa provides for analysis of ultrasonic waves of at least three transmitted center frequencies for tissue characterization, but requires assumptions about values of several key variables, including attenuation and the quality of the acoustic coupling at the tissue-transducer interface, both at each of the transmitted center frequencies. In addition, the Miwa system requires the transmission and analysis of a plurality of ultrasound signals having different transmitted center frequencies, wherein the tissue characterization is based upon energy as a function of the centers of the transmitted frequencies and of the ratios among the various energies.
Author, G. Guinta, in "Spectral Noise And Ultrasonic Tissue Characterization", Frontiers In Medical And Biological Imaging, Vol. 4, pages 209-217, 1992, teaches a modification of the Miwa method. Guinta considers a broadband ultrasound pulse containing a range of frequencies, and uses the Fourier Transform to separate the return into corresponding components. The transmitted energy at each frequency is determined by applying the same technique to the reflection from a metallic reference scatterer. For each frequency, Guinta obtains a normalized echo signal by dividing the corresponding Fourier energy (coefficient in the power spectrum) in the return from the tissue by that from the reference, a process equivalent to normalizing each of Miwa's returns by the corresponding transmitted power. Guinta's method still requires a reference plate and is thus subject to variations in transducer-tissue coupling and attenuation in the body throughout the range of frequencies used. Efforts to reduce this dependence by reducing the range of frequencies would also limit the amount of data received.
In summary, Guinta uses Fourier techniques to allow transmission and detection of a plurality of transmitted frequencies contained in a single pulse. These methods do not provide for direct measurement of reflectance through self-calibration, and thus in vivo use is still subject to calibration problems inherent in Miwa and in integrated backscatter methods.
In another prior art system, authors Sommer, Joynt, Carroll and Macovski ("Ultrasound characterization of abdominal tissues via digital analysis of backscattered wavefronts", Radiology, 141:811-7, 1981) used frequency domain (Fourier) analysis to determine the mean spacing of scatterers in the liver and spleen. Sommer et al. also studied the mean amplitude and variance of the amplitude ("amplitude domain analysis"); however, they did not offer solutions to the problem of assuming values for key variables. The amplitude in the Sommer et al. analysis depends heavily upon the variables of acoustic efficiency of the transducer and tissue absorption just as in IB analysis.
It is, therefore, an objective of the invention to provide an improved ultrasound tissue characterization system and method for quantifying and classifying the direct ultrasound data.
It is a further objective of the invention to provide an ultrasound tissue characterization system which requires neither an external reference point nor assumptions about crucial variables.